Marc De Gennes
Machine Learning Researcher at Callyope
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolMarc De Gennes is a machine learning researcher based in Paris with nine years of experience bridging quantitative biophysics and applied ML, currently focusing on speech-based biomarkers and foundation models at Callyope. He holds a PhD in Biophysics from UCL and has a strong track record modeling complex biological pattern formation, developing data-driven simulation methods and collaborating closely with experimental teams. Marc combines deep theoretical skills—statistical physics, PDE-based modeling and stochastic robustness—with practical engineering in Python, Matlab and C to turn experimental datasets into predictive models. His background in both wet-lab techniques and computational modeling gives him a rare perspective on how noise, mechanics and signaling couple in real systems, now applied to scalable ML problems in healthcare and signal analysis.
9 years of coding experience
1 year of employment as a software developer
Master's degree Statistical Physics and Soft Matter, Master's degree Statistical Physics and Soft Matter at Ecole normale supérieurePrépa PCSI-PC*, Prépa PCSI-PC* at Lycée Henri IVMaster's degree Engineering Physics, Master's degree Engineering Physics at École PolytechniqueUniversity College London
Github Skills (2)
bioinformatics2
dynamics1
Programming languages (1)
Github contributions (3)
marcdegennes/Artificial_Morphogen_Gradients
Jun 2020 - Nov 2020
Contributions:46 commits, 17 pushes, 1 branch in 4 months
marcdegennes/test
Aug 2018 - Aug 2018
learn
Contributions:2 PRs, 2 pushes, 3 branches in 1 day
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